The Influence of Technology on Social Network Analysis and Mining

Volume 6 of the series Lecture Notes in Social Networks pp 351-372


Extraction of Spatio-Temporal Data for Social Networks

  • Judith GelernterAffiliated withSchool of Computer Science, Carnegie-Mellon University Email author 
  • , Dong CaoAffiliated withSchool of Computer Science, Carnegie-Mellon University
  • , Kathleen M. CarleyAffiliated withSchool of Computer Science, Carnegie-Mellon University

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It is often possible to understand group change over time through examining social network data in a spatial and temporal context. Providing that context via text analysis requires identifying locations and associating them with people. Our GeoRef algorithm too automatically does this person-to-place mapping. It involves the identification of location, and uses syntactic proximity of words in the text to link location to person’s name. We describe an application using the algorithm based upon data from the Sudan Tribune divided into three periods in 2006 for the Darfur crisis. Contributions of this paper are (1) techniques to mine for location from text (2) techniques to mine for social network edges (associations between location and person), (3) spatio-temporal maps made from mined data, and (4) social network analysis based on mined data.